In [1]:
import requests
import os
import json
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
from matplotlib.pylab import rcParams
import seaborn as sns
In [2]:
#getting data from api
import requests
import json
shooting = requests.get("https://data.cityofnewyork.us/resource/833y-fsy8.json")
print(shooting.status_code)
json1 = shooting.json()
print(json1)
with open('shooting.json', 'w') as outfile:
      json.dump(json1, outfile)
shoot = pd.read_json('shooting.json')

200
[{'incident_key': '169180023', 'occur_date': '2017-09-09T00:00:00.000', 'occur_time': '3:57:00', 'boro': 'STATEN ISLAND', 'precinct': '120', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '959975', 'y_coord_cd': '171772', 'latitude': '40.63812599100004', 'longitude': '-74.08746692099999'}, {'incident_key': '169180027', 'occur_date': '2017-09-09T00:00:00.000', 'occur_time': '22:15:00', 'boro': 'BRONX', 'precinct': '50', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK HISPANIC', 'x_coord_cd': '1011288', 'y_coord_cd': '255912', 'latitude': '40.869060690000026', 'longitude': '-73.90224225899993'}, {'incident_key': '169180025', 'occur_date': '2017-09-09T00:00:00.000', 'occur_time': '18:35:00', 'boro': 'BROOKLYN', 'precinct': '79', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '999888', 'y_coord_cd': '193014', 'latitude': '40.69645001400005', 'longitude': '-73.94360673699998'}, {'incident_key': '169180024', 'occur_date': '2017-09-09T00:00:00.000', 'occur_time': '15:20:00', 'boro': 'BROOKLYN', 'precinct': '67', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '997784', 'y_coord_cd': '172132', 'latitude': '40.63913704300006', 'longitude': '-73.951236227'}, {'incident_key': '169180022', 'occur_date': '2017-09-09T00:00:00.000', 'occur_time': '0:20:00', 'boro': 'BROOKLYN', 'precinct': '61', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'ASIAN / PACIFIC ISLANDER', 'x_coord_cd': '1001019', 'y_coord_cd': '156467', 'latitude': '40.59613433800007', 'longitude': '-73.93961890199995'}, {'incident_key': '156603440', 'occur_date': '2016-09-09T00:00:00.000', 'occur_time': '20:58:00', 'boro': 'BROOKLYN', 'precinct': '67', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1003592', 'y_coord_cd': '176432', 'latitude': '40.65092883700004', 'longitude': '-73.93029673299998'}, {'incident_key': '156603439', 'occur_date': '2016-09-09T00:00:00.000', 'occur_time': '20:43:00', 'boro': 'BRONX', 'precinct': '41', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '1011370', 'y_coord_cd': '235889', 'latitude': '40.81410317400002', 'longitude': '-73.90202674799998'}, {'incident_key': '156603438', 'occur_date': '2016-09-09T00:00:00.000', 'occur_time': '11:50:00', 'boro': 'MANHATTAN', 'precinct': '32', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1001664', 'y_coord_cd': '239682', 'latitude': '40.82453835300004', 'longitude': '-73.93708114099996'}, {'incident_key': '156552658', 'occur_date': '2016-09-09T00:00:00.000', 'occur_time': '0:18:00', 'boro': 'QUEENS', 'precinct': '113', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1044416', 'y_coord_cd': '183458', 'latitude': '40.670030345000036', 'longitude': '-73.78311288699997'}, {'incident_key': '146014287', 'occur_date': '2015-09-09T00:00:00.000', 'occur_time': '23:08:00', 'boro': 'BRONX', 'precinct': '47', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1026323', 'y_coord_cd': '261252', 'latitude': '40.883658466000036', 'longitude': '-73.847847932'}, {'incident_key': '146014286', 'occur_date': '2015-09-09T00:00:00.000', 'occur_time': '23:00:00', 'boro': 'MANHATTAN', 'precinct': '28', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '998318', 'y_coord_cd': '231726', 'latitude': '40.80270731500008', 'longitude': '-73.94918758799997'}, {'incident_key': '146013532', 'occur_date': '2015-09-09T00:00:00.000', 'occur_time': '19:03:00', 'boro': 'BROOKLYN', 'precinct': '77', 'jurisdiction_code': '0', 'statistical_murder_flag': True, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1001196', 'y_coord_cd': '185003', 'latitude': '40.67445924500004', 'longitude': '-73.93890989599998'}, {'incident_key': '145992814', 'occur_date': '2015-09-09T00:00:00.000', 'occur_time': '11:54:00', 'boro': 'BROOKLYN', 'precinct': '70', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '994904', 'y_coord_cd': '167484', 'latitude': '40.62638319900003', 'longitude': '-73.96162067399997'}, {'incident_key': '138627598', 'occur_date': '2014-09-09T00:00:00.000', 'occur_time': '17:36:00', 'boro': 'BROOKLYN', 'precinct': '73', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1006587', 'y_coord_cd': '182075', 'latitude': '40.66641058000005', 'longitude': '-73.91948466499997'}, {'incident_key': '92525610', 'occur_date': '2013-09-09T00:00:00.000', 'occur_time': '5:26:00', 'boro': 'BROOKLYN', 'precinct': '75', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': True, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1015537', 'y_coord_cd': '178639', 'latitude': '40.65695242200008', 'longitude': '-73.88723913599993'}, {'incident_key': '92507649', 'occur_date': '2013-09-09T00:00:00.000', 'occur_time': '4:35:00', 'boro': 'BROOKLYN', 'precinct': '79', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '995342', 'y_coord_cd': '191876', 'latitude': '40.693333333000055', 'longitude': '-73.96000266999994'}, {'incident_key': '92507648', 'occur_date': '2013-09-09T00:00:00.000', 'occur_time': '3:55:00', 'boro': 'MANHATTAN', 'precinct': '17', 'jurisdiction_code': '0', 'location_desc': 'BAR/NIGHT CLUB', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '991876', 'y_coord_cd': '214311', 'latitude': '40.754915640000036', 'longitude': '-73.97247596599993'}, {'incident_key': '92525805', 'occur_date': '2013-09-09T00:00:00.000', 'occur_time': '15:14:00', 'boro': 'QUEENS', 'precinct': '113', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1050964', 'y_coord_cd': '189413', 'latitude': '40.686328495000055', 'longitude': '-73.75944958499997'}, {'incident_key': '86650273', 'occur_date': '2012-09-09T00:00:00.000', 'occur_time': '2:15:00', 'boro': 'QUEENS', 'precinct': '113', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1051505', 'y_coord_cd': '190826', 'latitude': '40.69020274700006', 'longitude': '-73.75748479699998'}, {'incident_key': '86650272', 'occur_date': '2012-09-09T00:00:00.000', 'occur_time': '2:01:00', 'boro': 'MANHATTAN', 'precinct': '28', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '997995', 'y_coord_cd': '230064', 'latitude': '40.79814608700008', 'longitude': '-73.95035767199995'}, {'incident_key': '86664788', 'occur_date': '2012-09-09T00:00:00.000', 'occur_time': '23:22:00', 'boro': 'STATEN ISLAND', 'precinct': '120', 'jurisdiction_code': '0', 'statistical_murder_flag': True, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '951991', 'y_coord_cd': '171198', 'latitude': '40.63652500300003', 'longitude': '-74.11623137199997'}, {'incident_key': '86651100', 'occur_date': '2012-09-09T00:00:00.000', 'occur_time': '15:47:00', 'boro': 'BROOKLYN', 'precinct': '77', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '998182', 'y_coord_cd': '186167', 'latitude': '40.677659418000076', 'longitude': '-73.94977317399997'}, {'incident_key': '80667853', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '23:00:00', 'boro': 'BRONX', 'precinct': '44', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'F', 'vic_race': 'BLACK', 'x_coord_cd': '1007977', 'y_coord_cd': '246029', 'latitude': '40.84194433400006', 'longitude': '-73.91424855599996'}, {'incident_key': '80667853', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '23:00:00', 'boro': 'BRONX', 'precinct': '44', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '18-24', 'vic_sex': 'F', 'vic_race': 'BLACK', 'x_coord_cd': '1007977', 'y_coord_cd': '246029', 'latitude': '40.84194433400006', 'longitude': '-73.91424855599996'}, {'incident_key': '80667853', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '23:00:00', 'boro': 'BRONX', 'precinct': '44', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1007977', 'y_coord_cd': '246029', 'latitude': '40.84194433400006', 'longitude': '-73.91424855599996'}, {'incident_key': '80667853', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '23:00:00', 'boro': 'BRONX', 'precinct': '44', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1007977', 'y_coord_cd': '246029', 'latitude': '40.84194433400006', 'longitude': '-73.91424855599996'}, {'incident_key': '80667641', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '22:43:00', 'boro': 'QUEENS', 'precinct': '104', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '1008657', 'y_coord_cd': '195934', 'latitude': '40.70444489000005', 'longitude': '-73.91197286999993'}, {'incident_key': '80667641', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '22:43:00', 'boro': 'QUEENS', 'precinct': '104', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'BLACK HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '1008657', 'y_coord_cd': '195934', 'latitude': '40.70444489000005', 'longitude': '-73.91197286999993'}, {'incident_key': '80655008', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '13:32:00', 'boro': 'BROOKLYN', 'precinct': '67', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '996921', 'y_coord_cd': '176967', 'latitude': '40.652409353000046', 'longitude': '-73.95433667599998'}, {'incident_key': '80654704', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '12:39:00', 'boro': 'QUEENS', 'precinct': '114', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1009725', 'y_coord_cd': '215121', 'latitude': '40.75710547500006', 'longitude': '-73.90804828499995'}, {'incident_key': '80653750', 'occur_date': '2011-09-09T00:00:00.000', 'occur_time': '0:25:00', 'boro': 'BROOKLYN', 'precinct': '67', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '999809', 'y_coord_cd': '172040', 'latitude': '40.63888119800004', 'longitude': '-73.94394003499998'}, {'incident_key': '74524209', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '2:42:00', 'boro': 'BRONX', 'precinct': '52', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK HISPANIC', 'x_coord_cd': '1016159', 'y_coord_cd': '255448', 'latitude': '40.86777088900004', 'longitude': '-73.88463279099993'}, {'incident_key': '74524209', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '2:42:00', 'boro': 'BRONX', 'precinct': '52', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK HISPANIC', 'x_coord_cd': '1016159', 'y_coord_cd': '255448', 'latitude': '40.86777088900004', 'longitude': '-73.88463279099993'}, {'incident_key': '74549230', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '22:00:00', 'boro': 'BRONX', 'precinct': '40', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK HISPANIC', 'x_coord_cd': '1005170', 'y_coord_cd': '235308', 'latitude': '40.812525348000065', 'longitude': '-73.92442689199999'}, {'incident_key': '74549231', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '20:28:00', 'boro': 'BROOKLYN', 'precinct': '81', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1001974', 'y_coord_cd': '191809', 'latitude': '40.69313863700007', 'longitude': '-73.93608724999996'}, {'incident_key': '74532192', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '17:07:00', 'boro': 'BROOKLYN', 'precinct': '71', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1000151', 'y_coord_cd': '180218', 'latitude': '40.66132742400004', 'longitude': '-73.94268848099993'}, {'incident_key': '74532192', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '17:07:00', 'boro': 'BROOKLYN', 'precinct': '71', 'jurisdiction_code': '0', 'statistical_murder_flag': True, 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1000151', 'y_coord_cd': '180218', 'latitude': '40.66132742400004', 'longitude': '-73.94268848099993'}, {'incident_key': '74530911', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '12:41:00', 'boro': 'BROOKLYN', 'precinct': '75', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1013511', 'y_coord_cd': '181454', 'latitude': '40.66468589900006', 'longitude': '-73.89452887499993'}, {'incident_key': '74530911', 'occur_date': '2010-09-09T00:00:00.000', 'occur_time': '12:41:00', 'boro': 'BROOKLYN', 'precinct': '75', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1013511', 'y_coord_cd': '181454', 'latitude': '40.66468589900006', 'longitude': '-73.89452887499993'}, {'incident_key': '65602677', 'occur_date': '2009-09-09T00:00:00.000', 'occur_time': '22:05:00', 'boro': 'QUEENS', 'precinct': '106', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': True, 'perp_age_group': '25-44', 'perp_sex': 'M', 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'vic_race': 'BLACK', 'x_coord_cd': '1018876', 'y_coord_cd': '241924', 'latitude': '40.83064129700006', 'longitude': '-73.87487918899996'}, {'incident_key': '65602676', 'occur_date': '2009-09-09T00:00:00.000', 'occur_time': '19:36:00', 'boro': 'BROOKLYN', 'precinct': '60', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'perp_age_group': 'UNKNOWN', 'perp_sex': 'U', 'perp_race': 'UNKNOWN', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '989392', 'y_coord_cd': '155078', 'latitude': '40.59233618200005', 'longitude': '-73.98148695899994'}, {'incident_key': '65575827', 'occur_date': '2009-09-09T00:00:00.000', 'occur_time': '14:45:00', 'boro': 'QUEENS', 'precinct': '101', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': 'UNKNOWN', 'perp_sex': 'U', 'perp_race': 'UNKNOWN', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1052809', 'y_coord_cd': 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'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1026255', 'y_coord_cd': '263724', 'latitude': '40.89044364500006', 'longitude': '-73.84807834399999'}, {'incident_key': '24474757', 'occur_date': '2006-09-24T00:00:00.000', 'occur_time': '18:35:00', 'boro': 'QUEENS', 'precinct': '105', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1057636', 'y_coord_cd': '203954', 'latitude': '40.72618713000002', 'longitude': '-73.73523390399998'}, {'incident_key': '24474756', 'occur_date': '2006-09-24T00:00:00.000', 'occur_time': '18:23:00', 'boro': 'QUEENS', 'precinct': '105', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1052128', 'y_coord_cd': '185997', 'latitude': '40.67694353600007', 'longitude': '-73.75528695999998'}, {'incident_key': '24491449', 'occur_date': '2006-09-24T00:00:00.000', 'occur_time': '17:10:00', 'boro': 'MANHATTAN', 'precinct': '33', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '999278', 'y_coord_cd': '244165', 'latitude': '40.83684728400005', 'longitude': '-73.94569219799997'}, {'incident_key': '24491446', 'occur_date': '2006-09-24T00:00:00.000', 'occur_time': '14:00:00', 'boro': 'BROOKLYN', 'precinct': '60', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': True, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'F', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '986860', 'y_coord_cd': '149123', 'latitude': '40.57599199300005', 'longitude': '-73.99060607299998'}, {'incident_key': '24474755', 'occur_date': '2006-09-24T00:00:00.000', 'occur_time': '13:59:00', 'boro': 'BRONX', 'precinct': '44', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1008455', 'y_coord_cd': '243215', 'latitude': '40.83421942500007', 'longitude': '-73.91253114899997'}, {'incident_key': '169680542', 'occur_date': '2017-09-23T00:00:00.000', 'occur_time': '19:25:00', 'boro': 'BRONX', 'precinct': '40', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1007373', 'y_coord_cd': '232752', 'latitude': '40.80550434700007', 'longitude': '-73.91647725199994'}, {'incident_key': '157022198', 'occur_date': '2016-09-23T00:00:00.000', 'occur_time': '13:50:00', 'boro': 'MANHATTAN', 'precinct': '32', 'jurisdiction_code': '0', 'statistical_murder_flag': True, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1000196', 'y_coord_cd': '237925', 'latitude': '40.81971865700007', 'longitude': '-73.94238949699997'}, {'incident_key': '146392728', 'occur_date': '2015-09-23T00:00:00.000', 'occur_time': '19:55:00', 'boro': 'MANHATTAN', 'precinct': '25', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1001375', 'y_coord_cd': '231978', 'latitude': '40.80339359100003', 'longitude': '-73.93814501199995'}, {'incident_key': '138849339', 'occur_date': '2014-09-23T00:00:00.000', 'occur_time': '21:04:00', 'boro': 'BROOKLYN', 'precinct': '71', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '995814', 'y_coord_cd': '181281', 'latitude': '40.66425185000002', 'longitude': '-73.95831877299997'}, {'incident_key': '138849338', 'occur_date': '2014-09-23T00:00:00.000', 'occur_time': '20:45:00', 'boro': 'BRONX', 'precinct': '46', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'BLACK HISPANIC', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '1011296', 'y_coord_cd': '248954', 'latitude': '40.84996305400006', 'longitude': '-73.90224140899994'}, {'incident_key': '138849337', 'occur_date': '2014-09-23T00:00:00.000', 'occur_time': '20:45:00', 'boro': 'BRONX', 'precinct': '44', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1008091', 'y_coord_cd': '243026', 'latitude': '40.833701665000035', 'longitude': '-73.91384721799993'}, {'incident_key': '92747298', 'occur_date': '2013-09-23T00:00:00.000', 'occur_time': '22:10:00', 'boro': 'QUEENS', 'precinct': '103', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1050771', 'y_coord_cd': '197489', 'latitude': '40.70849660900007', 'longitude': '-73.76006572499993'}, {'incident_key': '92747223', 'occur_date': '2013-09-23T00:00:00.000', 'occur_time': '21:00:00', 'boro': 'BRONX', 'precinct': '41', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK HISPANIC', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '1011607', 'y_coord_cd': '236142', 'latitude': '40.81479685700003', 'longitude': '-73.90116952199998'}, {'incident_key': '92747223', 'occur_date': '2013-09-23T00:00:00.000', 'occur_time': '21:00:00', 'boro': 'BRONX', 'precinct': '41', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '1011607', 'y_coord_cd': '236142', 'latitude': '40.81479685700003', 'longitude': '-73.90116952199998'}, {'incident_key': '92747299', 'occur_date': '2013-09-23T00:00:00.000', 'occur_time': '20:30:00', 'boro': 'BROOKLYN', 'precinct': '81', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1003127', 'y_coord_cd': '190619', 'latitude': '40.68986997800005', 'longitude': '-73.93193277299997'}, {'incident_key': '92747224', 'occur_date': '2013-09-23T00:00:00.000', 'occur_time': '16:55:00', 'boro': 'BROOKLYN', 'precinct': '69', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1009794', 'y_coord_cd': '171557', 'latitude': '40.63753230000003', 'longitude': '-73.90796443499994'}, {'incident_key': '92747225', 'occur_date': '2013-09-23T00:00:00.000', 'occur_time': '11:15:00', 'boro': 'BROOKLYN', 'precinct': '72', 'jurisdiction_code': '0', 'location_desc': 'JEWELRY STORE', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '45-64', 'vic_sex': 'M', 'vic_race': 'WHITE', 'x_coord_cd': '981791', 'y_coord_cd': '174817', 'latitude': '40.64651679000008', 'longitude': '-74.00886260099996'}, {'incident_key': '86876841', 'occur_date': '2012-09-23T00:00:00.000', 'occur_time': '5:20:00', 'boro': 'QUEENS', 'precinct': '114', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '<18', 'vic_sex': 'F', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '999484', 'y_coord_cd': '214810', 'latitude': '40.75627543400003', 'longitude': '-73.94501432899995'}, {'incident_key': '86877082', 'occur_date': '2012-09-23T00:00:00.000', 'occur_time': '5:13:00', 'boro': 'BROOKLYN', 'precinct': '73', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'vic_age_group': '45-64', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1009968', 'y_coord_cd': '182502', 'latitude': '40.667573424000075', 'longitude': '-73.90729576599993'}, {'incident_key': '86877081', 'occur_date': '2012-09-23T00:00:00.000', 'occur_time': '3:43:00', 'boro': 'BRONX', 'precinct': '41', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1014776', 'y_coord_cd': '237838', 'latitude': '40.81944151700003', 'longitude': '-73.88971325499993'}, {'incident_key': '86887457', 'occur_date': '2012-09-23T00:00:00.000', 'occur_time': '20:15:00', 'boro': 'BRONX', 'precinct': '46', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1007684', 'y_coord_cd': '248284', 'latitude': '40.84813442700005', 'longitude': '-73.91529962099996'}, {'incident_key': '86887457', 'occur_date': '2012-09-23T00:00:00.000', 'occur_time': '20:15:00', 'boro': 'BRONX', 'precinct': '46', 'jurisdiction_code': '0', 'location_desc': 'MULTI DWELL - APT BUILD', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1007684', 'y_coord_cd': '248284', 'latitude': '40.84813442700005', 'longitude': '-73.91529962099996'}, {'incident_key': '86887456', 'occur_date': '2012-09-23T00:00:00.000', 'occur_time': '19:15:00', 'boro': 'QUEENS', 'precinct': '113', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '18-24', 'perp_sex': 'M', 'perp_race': 'BLACK', 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1052235', 'y_coord_cd': '192115', 'latitude': '40.69373516400003', 'longitude': '-73.75483947599997'}, {'incident_key': '86877542', 'occur_date': '2012-09-23T00:00:00.000', 'occur_time': '17:25:00', 'boro': 'BROOKLYN', 'precinct': '75', 'jurisdiction_code': '2', 'location_desc': 'MULTI DWELL - PUBLIC HOUS', 'statistical_murder_flag': False, 'perp_age_group': '<18', 'perp_sex': 'M', 'perp_race': 'WHITE HISPANIC', 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK HISPANIC', 'x_coord_cd': '1019411', 'y_coord_cd': '182616', 'latitude': '40.66785386400005', 'longitude': '-73.87325602999994'}, {'incident_key': '80855402', 'occur_date': '2011-09-23T00:00:00.000', 'occur_time': '4:23:00', 'boro': 'BROOKLYN', 'precinct': '71', 'jurisdiction_code': '0', 'statistical_murder_flag': True, 'vic_age_group': '18-24', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '997874', 'y_coord_cd': '180875', 'latitude': '40.66313454000005', 'longitude': '-73.95089428399997'}, {'incident_key': '80871012', 'occur_date': '2011-09-23T00:00:00.000', 'occur_time': '23:07:00', 'boro': 'BRONX', 'precinct': '43', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK HISPANIC', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'ASIAN / PACIFIC ISLANDER', 'x_coord_cd': '1019931', 'y_coord_cd': '241419', 'latitude': '40.829251019000026', 'longitude': '-73.87106959999993'}, {'incident_key': '80871012', 'occur_date': '2011-09-23T00:00:00.000', 'occur_time': '23:07:00', 'boro': 'BRONX', 'precinct': '43', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'perp_age_group': '25-44', 'perp_sex': 'M', 'perp_race': 'BLACK HISPANIC', 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK HISPANIC', 'x_coord_cd': '1019931', 'y_coord_cd': '241419', 'latitude': '40.829251019000026', 'longitude': '-73.87106959999993'}, {'incident_key': '80871242', 'occur_date': '2011-09-23T00:00:00.000', 'occur_time': '16:02:00', 'boro': 'STATEN ISLAND', 'precinct': '120', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '65+', 'vic_sex': 'M', 'vic_race': 'WHITE HISPANIC', 'x_coord_cd': '950823', 'y_coord_cd': '170806', 'latitude': '40.63544471700004', 'longitude': '-74.12043775599993'}, {'incident_key': '80858969', 'occur_date': '2011-09-23T00:00:00.000', 'occur_time': '0:04:00', 'boro': 'BROOKLYN', 'precinct': '62', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'WHITE', 'x_coord_cd': '987500', 'y_coord_cd': '162411', 'latitude': '40.61246467600006', 'longitude': '-73.98829583799994'}, {'incident_key': '74758971', 'occur_date': '2010-09-23T00:00:00.000', 'occur_time': '19:58:00', 'boro': 'BROOKLYN', 'precinct': '83', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK HISPANIC', 'x_coord_cd': '1001561', 'y_coord_cd': '194033', 'latitude': '40.69924381800007', 'longitude': '-73.93757084499998'}, {'incident_key': '74752729', 'occur_date': '2010-09-23T00:00:00.000', 'occur_time': '18:45:00', 'boro': 'QUEENS', 'precinct': '103', 'jurisdiction_code': '0', 'statistical_murder_flag': True, 'vic_age_group': '18-24', 'vic_sex': 'F', 'vic_race': 'BLACK', 'x_coord_cd': '1039650', 'y_coord_cd': '192700', 'latitude': '40.69542857600004', 'longitude': '-73.80021748999997'}, {'incident_key': '74752729', 'occur_date': '2010-09-23T00:00:00.000', 'occur_time': '18:45:00', 'boro': 'QUEENS', 'precinct': '103', 'jurisdiction_code': '0', 'statistical_murder_flag': True, 'vic_age_group': '25-44', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1039650', 'y_coord_cd': '192700', 'latitude': '40.69542857600004', 'longitude': '-73.80021748999997'}, {'incident_key': '74752845', 'occur_date': '2010-09-23T00:00:00.000', 'occur_time': '18:30:00', 'boro': 'BRONX', 'precinct': '42', 'jurisdiction_code': '0', 'statistical_murder_flag': False, 'vic_age_group': '<18', 'vic_sex': 'M', 'vic_race': 'BLACK', 'x_coord_cd': '1012059', 'y_coord_cd': '244779', 'latitude': '40.83850153900005', 'longitude': '-73.89950079699997'}]
In [3]:
from pymongo import MongoClient
client=MongoClient("mongodb+srv://vijit:test@cluster0-xl7d3.mongodb.net/test?retryWrites=true&w=majority")

db=client.get_database('vijit_db')
db
records=db.shooting
records.insert_many(shoot.to_dict('records'))
Out[3]:
<pymongo.results.InsertManyResult at 0x1a21ec7690>
In [4]:
shoot.head()
Out[4]:
incident_key occur_date occur_time boro precinct jurisdiction_code statistical_murder_flag vic_age_group vic_sex vic_race x_coord_cd y_coord_cd latitude longitude location_desc perp_age_group perp_sex perp_race
0 169180023 2017-09-09T00:00:00.000 2019-12-14 03:57:00 STATEN ISLAND 120 0 False 25-44 M BLACK 959975 171772 40.638126 -74.087467 NaN NaN NaN NaN
1 169180027 2017-09-09T00:00:00.000 2019-12-14 22:15:00 BRONX 50 0 False 25-44 M BLACK HISPANIC 1011288 255912 40.869061 -73.902242 NaN NaN NaN NaN
2 169180025 2017-09-09T00:00:00.000 2019-12-14 18:35:00 BROOKLYN 79 2 False 18-24 M BLACK 999888 193014 40.696450 -73.943607 MULTI DWELL - PUBLIC HOUS NaN NaN NaN
3 169180024 2017-09-09T00:00:00.000 2019-12-14 15:20:00 BROOKLYN 67 0 False 18-24 M BLACK 997784 172132 40.639137 -73.951236 NaN 18-24 M BLACK
4 169180022 2017-09-09T00:00:00.000 2019-12-14 00:20:00 BROOKLYN 61 2 False 25-44 M ASIAN / PACIFIC ISLANDER 1001019 156467 40.596134 -73.939619 MULTI DWELL - PUBLIC HOUS NaN NaN NaN
In [5]:
shoot.isnull().sum() #checking for null values
Out[5]:
incident_key                 0
occur_date                   0
occur_time                   0
boro                         0
precinct                     0
jurisdiction_code            0
statistical_murder_flag      0
vic_age_group                0
vic_sex                      0
vic_race                     0
x_coord_cd                   0
y_coord_cd                   0
latitude                     0
longitude                    0
location_desc              608
perp_age_group             352
perp_sex                   352
perp_race                  352
dtype: int64
In [6]:
#heatmap to show missing values
sns.heatmap(shoot.isnull(),yticklabels=False,cbar=False,cmap="YlGnBu")
#plt.savefig("figure1.png") 
#plt.savefig('sample.pdf')
Out[6]:
<matplotlib.axes._subplots.AxesSubplot at 0x1a21c1d1d0>
In [7]:
shoot['incident_key'].value_counts #counting unique values
#here incident key says- it can have values of mulitple victims involved and duplicate values are produced.
#but here we dont have any duplicate values
Out[7]:
<bound method IndexOpsMixin.value_counts of 0      169180023
1      169180027
2      169180025
3      169180024
4      169180022
         ...    
995     80858969
996     74758971
997     74752729
998     74752729
999     74752845
Name: incident_key, Length: 1000, dtype: int64>
In [8]:
shoot.drop(['incident_key'], axis = 1,inplace = True )
In [9]:
shoot.head(5)
Out[9]:
occur_date occur_time boro precinct jurisdiction_code statistical_murder_flag vic_age_group vic_sex vic_race x_coord_cd y_coord_cd latitude longitude location_desc perp_age_group perp_sex perp_race
0 2017-09-09T00:00:00.000 2019-12-14 03:57:00 STATEN ISLAND 120 0 False 25-44 M BLACK 959975 171772 40.638126 -74.087467 NaN NaN NaN NaN
1 2017-09-09T00:00:00.000 2019-12-14 22:15:00 BRONX 50 0 False 25-44 M BLACK HISPANIC 1011288 255912 40.869061 -73.902242 NaN NaN NaN NaN
2 2017-09-09T00:00:00.000 2019-12-14 18:35:00 BROOKLYN 79 2 False 18-24 M BLACK 999888 193014 40.696450 -73.943607 MULTI DWELL - PUBLIC HOUS NaN NaN NaN
3 2017-09-09T00:00:00.000 2019-12-14 15:20:00 BROOKLYN 67 0 False 18-24 M BLACK 997784 172132 40.639137 -73.951236 NaN 18-24 M BLACK
4 2017-09-09T00:00:00.000 2019-12-14 00:20:00 BROOKLYN 61 2 False 25-44 M ASIAN / PACIFIC ISLANDER 1001019 156467 40.596134 -73.939619 MULTI DWELL - PUBLIC HOUS NaN NaN NaN
In [10]:
#count the total number of null values in location_desc
shoot['location_desc'].value_counts(dropna=False) #dropna equal to false will show the null values
Out[10]:
NaN                          608
MULTI DWELL - PUBLIC HOUS    160
MULTI DWELL - APT BUILD      138
PVT HOUSE                     35
GROCERY/BODEGA                16
COMMERCIAL BLDG                9
BAR/NIGHT CLUB                 6
RESTAURANT/DINER               6
FAST FOOD                      5
DRY CLEANER/LAUNDRY            3
SHOE STORE                     3
BEAUTY/NAIL SALON              2
CLOTHING BOUTIQUE              2
CANDY STORE                    1
SUPERMARKET                    1
JEWELRY STORE                  1
STORE UNCLASSIFIED             1
GAS STATION                    1
VARIETY STORE                  1
STORAGE FACILITY               1
Name: location_desc, dtype: int64
In [11]:
shoot['location_desc'].ffill(inplace=True)
In [12]:
shoot['location_desc'].head(5)
Out[12]:
0                          NaN
1                          NaN
2    MULTI DWELL - PUBLIC HOUS
3    MULTI DWELL - PUBLIC HOUS
4    MULTI DWELL - PUBLIC HOUS
Name: location_desc, dtype: object
In [13]:
shoot['location_desc'].bfill(inplace=True)
In [14]:
#count the total number of null values in location_desc
shoot['location_desc'].value_counts(dropna=False) #dropna equal to false will show the null values
Out[14]:
MULTI DWELL - PUBLIC HOUS    476
MULTI DWELL - APT BUILD      317
PVT HOUSE                     70
GROCERY/BODEGA                35
BAR/NIGHT CLUB                30
COMMERCIAL BLDG               22
RESTAURANT/DINER               9
STORAGE FACILITY               7
FAST FOOD                      7
DRY CLEANER/LAUNDRY            6
STORE UNCLASSIFIED             5
SHOE STORE                     3
BEAUTY/NAIL SALON              3
SUPERMARKET                    3
GAS STATION                    2
CLOTHING BOUTIQUE              2
JEWELRY STORE                  1
CANDY STORE                    1
VARIETY STORE                  1
Name: location_desc, dtype: int64
In [15]:
shoot.isnull().sum() #checking for null values
Out[15]:
occur_date                   0
occur_time                   0
boro                         0
precinct                     0
jurisdiction_code            0
statistical_murder_flag      0
vic_age_group                0
vic_sex                      0
vic_race                     0
x_coord_cd                   0
y_coord_cd                   0
latitude                     0
longitude                    0
location_desc                0
perp_age_group             352
perp_sex                   352
perp_race                  352
dtype: int64
In [16]:
# dealing with perp_sex and perp_race
shoot['perp_sex'].unique()
Out[16]:
array([nan, 'M', 'U', 'F'], dtype=object)
In [17]:
shoot['perp_race'].unique()
Out[17]:
array([nan, 'BLACK', 'WHITE HISPANIC', 'BLACK HISPANIC', 'WHITE',
       'UNKNOWN', 'ASIAN / PACIFIC ISLANDER'], dtype=object)
In [18]:
#countplot of perp_sex
sns.countplot(x='perp_sex',data=shoot)
Out[18]:
<matplotlib.axes._subplots.AxesSubplot at 0x1a21c36990>
In [19]:
# dealing with perp_sex missing values
shoot['perp_sex'].ffill(inplace=True)
shoot['perp_sex'].bfill(inplace=True)
shoot['perp_sex'].isnull().sum()
Out[19]:
0
In [20]:
sns.countplot(x='perp_sex',data=shoot)
Out[20]:
<matplotlib.axes._subplots.AxesSubplot at 0x1a21c49910>
In [21]:
#Dealing with missing values
shoot = shoot.fillna({
        'perp_race' : 'UNKNOWN',
})
In [22]:
shoot['perp_race'].unique()
Out[22]:
array(['UNKNOWN', 'BLACK', 'WHITE HISPANIC', 'BLACK HISPANIC', 'WHITE',
       'ASIAN / PACIFIC ISLANDER'], dtype=object)
In [23]:
shoot.isnull().sum()
Out[23]:
occur_date                   0
occur_time                   0
boro                         0
precinct                     0
jurisdiction_code            0
statistical_murder_flag      0
vic_age_group                0
vic_sex                      0
vic_race                     0
x_coord_cd                   0
y_coord_cd                   0
latitude                     0
longitude                    0
location_desc                0
perp_age_group             352
perp_sex                     0
perp_race                    0
dtype: int64
In [24]:
shoot['perp_age_group'].unique()
Out[24]:
array([nan, '18-24', '25-44', '<18', 'UNKNOWN', '45-64', '65+'],
      dtype=object)
In [25]:
#creating a function and categorizing every object in the perp_age_group 
def perp_age(x):
    if x=='<18':
        return 0
    if x=='18-24':
        return 1
    if x=='25-44':
        return 2
    if x=='45-64':
        return 3
    if x=='65+':
        return 4
    if x=='UNKNOWN':
        return 5
In [26]:
shoot['perp_age_group']=shoot['perp_age_group'].apply(perp_age)
In [27]:
shoot.isnull().sum()
Out[27]:
occur_date                   0
occur_time                   0
boro                         0
precinct                     0
jurisdiction_code            0
statistical_murder_flag      0
vic_age_group                0
vic_sex                      0
vic_race                     0
x_coord_cd                   0
y_coord_cd                   0
latitude                     0
longitude                    0
location_desc                0
perp_age_group             352
perp_sex                     0
perp_race                    0
dtype: int64
In [28]:
shoot['boro'].unique()
Out[28]:
array(['STATEN ISLAND', 'BRONX', 'BROOKLYN', 'MANHATTAN', 'QUEENS'],
      dtype=object)
In [29]:
#checking for perp_age_group count in boro to replace missing values
sns.boxplot(x='boro',y='perp_age_group',data=shoot)
Out[29]:
<matplotlib.axes._subplots.AxesSubplot at 0x1a21c5bd50>
In [30]:
#imputing age values with taking mean using box plot according to boro
def imputing_age(col):
    perp_age_group = col[0]
    boro =col[1]
    
    if pd.isnull(perp_age_group):
        if boro == 'BROOKLYN':
            return 3
        elif boro == 'QUEENS':
            return 3
        else:
            return 2
    else:
        return perp_age_group
In [31]:
#imputing the values to fill null values
shoot['perp_age_group']=shoot[['perp_age_group','boro']].apply(imputing_age,axis=1)
In [32]:
shoot.head(2)
Out[32]:
occur_date occur_time boro precinct jurisdiction_code statistical_murder_flag vic_age_group vic_sex vic_race x_coord_cd y_coord_cd latitude longitude location_desc perp_age_group perp_sex perp_race
0 2017-09-09T00:00:00.000 2019-12-14 03:57:00 STATEN ISLAND 120 0 False 25-44 M BLACK 959975 171772 40.638126 -74.087467 MULTI DWELL - PUBLIC HOUS 2.0 M UNKNOWN
1 2017-09-09T00:00:00.000 2019-12-14 22:15:00 BRONX 50 0 False 25-44 M BLACK HISPANIC 1011288 255912 40.869061 -73.902242 MULTI DWELL - PUBLIC HOUS 2.0 M UNKNOWN
In [33]:
shoot['perp_age_group']=shoot['perp_age_group'].astype(int)
In [34]:
shoot['occur_date'] = pd.to_datetime(shoot.occur_date)#converting occur_date from object to datetime
shoot['occur_time'] = pd.to_datetime(shoot.occur_time)
shoot.dtypes
Out[34]:
occur_date                 datetime64[ns]
occur_time                 datetime64[ns]
boro                               object
precinct                            int64
jurisdiction_code                   int64
statistical_murder_flag              bool
vic_age_group                      object
vic_sex                            object
vic_race                           object
x_coord_cd                          int64
y_coord_cd                          int64
latitude                          float64
longitude                         float64
location_desc                      object
perp_age_group                      int64
perp_sex                           object
perp_race                          object
dtype: object
In [35]:
#convertin vic_age_group from object to int
shoot['vic_age_group'].unique()
Out[35]:
array(['25-44', '18-24', '<18', '45-64', '65+', 'UNKNOWN'], dtype=object)
In [36]:
#creating to function to categorize values
def vic_age(x):
    if x=='<18':
        return 0
    if x=='18-24':
        return 1
    if x=='25-44':
        return 2
    if x=='45-64':
        return 3
    if x=='65+':
        return 4
    if x=='UNKNOWN':
        return 5
In [37]:
shoot['vic_age_group']=shoot['vic_age_group'].apply(vic_age)
In [38]:
shoot['vic_age_group']=shoot['vic_age_group'].astype(int)
In [39]:
#getting hour from date time and dropping the occur_time column
shoot['shooting_hour']=shoot.occur_time.dt.hour
shoot.drop('occur_time',axis=1,inplace=True)
In [40]:
#getting month, year and Day from the occur_date column and dropping occur_date column
shoot['Year']=shoot.occur_date.dt.year
shoot['Month']=shoot.occur_date.dt.month
shoot['Day'] = shoot.occur_date.dt.day
shoot.drop(['occur_date'], axis = 1,inplace = True )
In [41]:
shoot.drop(['statistical_murder_flag'], axis = 1,inplace = True )
In [42]:
shoot.head(2)
Out[42]:
boro precinct jurisdiction_code vic_age_group vic_sex vic_race x_coord_cd y_coord_cd latitude longitude location_desc perp_age_group perp_sex perp_race shooting_hour Year Month Day
0 STATEN ISLAND 120 0 2 M BLACK 959975 171772 40.638126 -74.087467 MULTI DWELL - PUBLIC HOUS 2 M UNKNOWN 3 2017 9 9
1 BRONX 50 0 2 M BLACK HISPANIC 1011288 255912 40.869061 -73.902242 MULTI DWELL - PUBLIC HOUS 2 M UNKNOWN 22 2017 9 9
In [43]:
shoot.dtypes
Out[43]:
boro                  object
precinct               int64
jurisdiction_code      int64
vic_age_group          int64
vic_sex               object
vic_race              object
x_coord_cd             int64
y_coord_cd             int64
latitude             float64
longitude            float64
location_desc         object
perp_age_group         int64
perp_sex              object
perp_race             object
shooting_hour          int64
Year                   int64
Month                  int64
Day                    int64
dtype: object
In [44]:
shoot['location_desc'].unique()
Out[44]:
array(['MULTI DWELL - PUBLIC HOUS', 'MULTI DWELL - APT BUILD',
       'BAR/NIGHT CLUB', 'SHOE STORE', 'PVT HOUSE', 'GROCERY/BODEGA',
       'FAST FOOD', 'RESTAURANT/DINER', 'COMMERCIAL BLDG',
       'STORE UNCLASSIFIED', 'GAS STATION', 'DRY CLEANER/LAUNDRY',
       'CANDY STORE', 'VARIETY STORE', 'STORAGE FACILITY', 'SUPERMARKET',
       'BEAUTY/NAIL SALON', 'CLOTHING BOUTIQUE', 'JEWELRY STORE'],
      dtype=object)
In [45]:
#dealing with location_desc
shoot['location_desc']= shoot.location_desc.str.replace('MULTI DWELL - ','')
shoot['location_desc']= shoot.location_desc.str.replace('PUBLIC HOUS','PUBLIC HOUSE')
In [46]:
shoot.head()
Out[46]:
boro precinct jurisdiction_code vic_age_group vic_sex vic_race x_coord_cd y_coord_cd latitude longitude location_desc perp_age_group perp_sex perp_race shooting_hour Year Month Day
0 STATEN ISLAND 120 0 2 M BLACK 959975 171772 40.638126 -74.087467 PUBLIC HOUSE 2 M UNKNOWN 3 2017 9 9
1 BRONX 50 0 2 M BLACK HISPANIC 1011288 255912 40.869061 -73.902242 PUBLIC HOUSE 2 M UNKNOWN 22 2017 9 9
2 BROOKLYN 79 2 1 M BLACK 999888 193014 40.696450 -73.943607 PUBLIC HOUSE 3 M UNKNOWN 18 2017 9 9
3 BROOKLYN 67 0 1 M BLACK 997784 172132 40.639137 -73.951236 PUBLIC HOUSE 1 M BLACK 15 2017 9 9
4 BROOKLYN 61 2 2 M ASIAN / PACIFIC ISLANDER 1001019 156467 40.596134 -73.939619 PUBLIC HOUSE 3 M UNKNOWN 0 2017 9 9
In [47]:
#checking null values before visualization
shoot.isnull().sum()
Out[47]:
boro                 0
precinct             0
jurisdiction_code    0
vic_age_group        0
vic_sex              0
vic_race             0
x_coord_cd           0
y_coord_cd           0
latitude             0
longitude            0
location_desc        0
perp_age_group       0
perp_sex             0
perp_race            0
shooting_hour        0
Year                 0
Month                0
Day                  0
dtype: int64
In [48]:
sns.countplot(x='jurisdiction_code',data=shoot)
Out[48]:
<matplotlib.axes._subplots.AxesSubplot at 0x1a21c97490>
In [49]:
import matplotlib.gridspec as gridspec

# Create 2x2 sub plots
gs = gridspec.GridSpec(2, 2)
plt.figure(figsize=(18,10))
ax = plt.subplot(gs[0, 0]) # row 0, col 0
sns.countplot(x='Year',data=shoot)
ax = plt.subplot(gs[0, 1]) # row 0, col 1
sns.countplot(x='Day',data=shoot)
ax = plt.subplot(gs[1, :]) # row 1, span all columns
sns.countplot(x='Month',data=shoot)
Out[49]:
<matplotlib.axes._subplots.AxesSubplot at 0x1a21c7db10>
In [50]:
#dropping columns which are not useful #month is only a single value i.e 9
shoot.drop(['x_coord_cd','y_coord_cd','latitude','longitude','Month'], axis = 1,inplace = True )
In [51]:
shoot.dtypes
Out[51]:
boro                 object
precinct              int64
jurisdiction_code     int64
vic_age_group         int64
vic_sex              object
vic_race             object
location_desc        object
perp_age_group        int64
perp_sex             object
perp_race            object
shooting_hour         int64
Year                  int64
Day                   int64
dtype: object
In [52]:
#converting the file to csv
#shoot.to_csv(r'/Users/vijitchekkala/Desktop/shooting_cleaned_1.csv')
In [53]:
import psycopg2
In [54]:
#creating shooting database in postgres
try:
    dbConnection = psycopg2.connect(
        user = "dap",
        password = "dap",
        host = "192.168.56.30",
        port = "5432",
        database = "postgres")
    dbConnection.set_isolation_level(0) # AUTOCOMMIT
    dbCursor = dbConnection.cursor()
    dbCursor.execute('CREATE DATABASE shooting;')
    dbCursor.close()
except (Exception , psycopg2.Error) as dbError :
    print ("Error while connecting to PostgreSQL", dbError)
finally:
    if(dbConnection): dbConnection.close()

Error while connecting to PostgreSQL database "shooting" already exists
In [55]:
# Creating Tables 
try:
    dbConnection = psycopg2.connect(
    user = "dap",
    password = "dap",
    host = "192.168.56.30",
    port = "5432",
    database = "shooting")
    dbConnection.set_isolation_level(0) # AUTOCOMMIT
    dbCursor = dbConnection.cursor()
    dbCursor.execute("""
    CREATE TABLE test4(
        boro varchar(255),
        precinct numeric(8,2),
        jurisdiction_code numeric(5,1),
        statistical_murder_flag bool,
        vice_age_group numeric(5,1),
        vice_sex  varchar(255),
        vice_race varchar(255),
        location_desc varchar(255),
        perp_age_group numeric(5,1),
        perp_sex varchar(255),
        perp_race varchar(255),
        shooting_hour int,
        year int,
        Day int
        );
    """)
    #dbCursor.execute("SET datestyle TO dmy ")
    dbCursor.close()
except (Exception , psycopg2.Error) as dbError :
    print ("Error while connecting to PostgreSQL", dbError)
finally:
    if(dbConnection): dbConnection.close()

Error while connecting to PostgreSQL relation "test4" already exists
In [56]:
# Inserting our csv file into our created postgres database
import csv
try:
    dbConnection = psycopg2.connect(
        user = "dap",
        password = "dap",
        host = "192.168.56.30",
        port = "5432",
        database = "shooting")
    dbConnection.set_isolation_level(0) # AUTOCOMMIT
    dbCursor = dbConnection.cursor()
    with open('/users/vijitchekkala/Desktop/python_final.csv', 'r') as f:
        read = csv.reader(f)
        next(read)
        #dbCursor.copy_from(f, 'criminalcourts5', sep=',')
        for row in read:
            dbCursor.execute("INSERT INTO test4 VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)",row)
        dbConnection.commit() 
        
    dbCursor.close()
except (Exception , psycopg2.Error) as dbError :
    print ("Error:", dbError)
finally:
    if(dbConnection): dbConnection.close()
In [57]:
import pandas as pd
import pandas.io.sql as sqlio
import psycopg2
sql = "SELECT * from test4"
try:
    dbConnection = psycopg2.connect(
    user = "dap",
    password = "dap",
    host = "192.168.56.30",
    port = "5432",
    database = "shooting")
    shooting = sqlio.read_sql_query(sql, dbConnection)
except (Exception , psycopg2.Error) as dbError :
    print("Error:", dbError)
finally:
    if(dbConnection): dbConnection.close()
In [58]:
shooting.head(2)
Out[58]:
boro precinct jurisdiction_code statistical_murder_flag vice_age_group vice_sex vice_race location_desc perp_age_group perp_sex perp_race shooting_hour year day
0 STATEN ISLAND 120.0 0.0 False 2.0 M BLACK PUBLIC HOUSE 2.0 M UNKNOWN 3 2017 9
1 BRONX 50.0 0.0 False 2.0 M BLACK HISPANIC PUBLIC HOUSE 2.0 M UNKNOWN 22 2017 9
In [59]:
shooting.dtypes
Out[59]:
boro                        object
precinct                   float64
jurisdiction_code          float64
statistical_murder_flag       bool
vice_age_group             float64
vice_sex                    object
vice_race                   object
location_desc               object
perp_age_group             float64
perp_sex                    object
perp_race                   object
shooting_hour                int64
year                         int64
day                          int64
dtype: object
In [60]:
shooting["jurisdiction_code"] = shooting["jurisdiction_code"].astype('category')
shooting["perp_age_group"] = shooting["perp_age_group"].astype('category')
shooting["perp_sex"] = shooting["perp_sex"].astype('category')
shooting["perp_race"] = shooting["perp_race"].astype('category')
shooting['precinct']=shooting['precinct'].astype('int')
In [61]:
shooting.dtypes
Out[61]:
boro                         object
precinct                      int64
jurisdiction_code          category
statistical_murder_flag        bool
vice_age_group              float64
vice_sex                     object
vice_race                    object
location_desc                object
perp_age_group             category
perp_sex                   category
perp_race                  category
shooting_hour                 int64
year                          int64
day                           int64
dtype: object
In [62]:
#visualization
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from matplotlib.pylab import rcParams
import seaborn as sns
import plotly.express as px
from plotly.offline import iplot
from plotly import tools
import plotly.graph_objects as go
import plotly.express as px
import plotly.offline as py
import plotly.figure_factory as ff
In [63]:
#heatmap to show correlation
plt.figure(figsize=(16,10))
sns.heatmap(shooting.corr(),annot=True,cmap='Greens')
plt.title('Heatmap of co-relation between variables',fontsize=14)
plt.show()
In [64]:
shooting.dtypes
Out[64]:
boro                         object
precinct                      int64
jurisdiction_code          category
statistical_murder_flag        bool
vice_age_group              float64
vice_sex                     object
vice_race                    object
location_desc                object
perp_age_group             category
perp_sex                   category
perp_race                  category
shooting_hour                 int64
year                          int64
day                           int64
dtype: object
In [65]:
fig = px.scatter(shooting, x="shooting_hour", y='location_desc', color="location_desc")
layout = go.Layout(
    title=go.layout.Title(
        text="Shooting hours at different locations",
        x=0.6
    ),
    font=dict(size=14),
    width=800,
    height=600,
    showlegend=False
)
fig.update_layout(layout)
fig.show()
In [70]:
#visualizing shooting year with boro
plt.figure(figsize=(18,10))
sns.countplot(x='year',hue='boro',data=shooting,edgecolor=sns.color_palette("dark",3),
              palette="Set2").set_title("Number of shooting incidents in borough with years",fontsize=18)
Out[70]:
Text(0.5, 1.0, 'Number of shooting incidents in borough with years')
In [71]:
#count perp_sex
sns.countplot(x='perp_sex',data=shoot,color='grey',palette=["#7fcdbb"])
Out[71]:
<matplotlib.axes._subplots.AxesSubplot at 0x1c279c2f10>
In [72]:
shooting.head(10)
Out[72]:
boro precinct jurisdiction_code statistical_murder_flag vice_age_group vice_sex vice_race location_desc perp_age_group perp_sex perp_race shooting_hour year day
0 STATEN ISLAND 120 0.0 False 2.0 M BLACK PUBLIC HOUSE 2.0 M UNKNOWN 3 2017 9
1 BRONX 50 0.0 False 2.0 M BLACK HISPANIC PUBLIC HOUSE 2.0 M UNKNOWN 22 2017 9
2 BROOKLYN 79 2.0 False 1.0 M BLACK PUBLIC HOUSE 3.0 M UNKNOWN 18 2017 9
3 BROOKLYN 67 0.0 False 1.0 M BLACK PUBLIC HOUSE 1.0 M BLACK 15 2017 9
4 BROOKLYN 61 2.0 False 2.0 M ASIAN / PACIFIC ISLANDER PUBLIC HOUSE 3.0 M UNKNOWN 0 2017 9
5 BROOKLYN 67 0.0 False 0.0 M BLACK APT BUILD 2.0 M BLACK 20 2016 9
6 BRONX 41 0.0 False 2.0 M WHITE HISPANIC APT BUILD 2.0 M UNKNOWN 20 2016 9
7 MANHATTAN 32 0.0 False 0.0 M BLACK APT BUILD 2.0 M UNKNOWN 11 2016 9
8 QUEENS 113 0.0 False 2.0 M BLACK APT BUILD 3.0 M UNKNOWN 0 2016 9
9 BRONX 47 2.0 False 2.0 M BLACK PUBLIC HOUSE 2.0 M UNKNOWN 23 2015 9
In [73]:
shooting['precinct'].unique() #dropna equal to false will show the null values
Out[73]:
array([120,  50,  79,  67,  61,  41,  32, 113,  47,  28,  77,  70,  73,
        75,  17,  44, 104, 114,  52,  40,  81,  71, 106,  43,  60, 101,
       103,  42, 105, 115,  83,  34,  84, 109,  88,  30,  46,  23,  33,
        69,  90,  49, 122,  94, 121, 100,  26, 107,  48,  66,  63, 102,
        20,  25,  24,  45,   7, 110,  72,  68,   9,  76,   1,  18,  78,
        13,   5,  62,  10])
In [74]:
shooting.shape
Out[74]:
(2000, 14)
In [75]:
shooting.corr()
Out[75]:
precinct statistical_murder_flag vice_age_group shooting_hour year day
precinct 1.000000 -0.013313 0.027866 -0.052582 0.007797 -0.110892
statistical_murder_flag -0.013313 1.000000 0.114563 -0.014742 -0.036075 0.014697
vice_age_group 0.027866 0.114563 1.000000 0.057020 0.025933 -0.013749
shooting_hour -0.052582 -0.014742 0.057020 1.000000 0.061158 0.079887
year 0.007797 -0.036075 0.025933 0.061158 1.000000 -0.051156
day -0.110892 0.014697 -0.013749 0.079887 -0.051156 1.000000
In [76]:
shooting['boro'].unique()
Out[76]:
array(['STATEN ISLAND', 'BRONX', 'BROOKLYN', 'MANHATTAN', 'QUEENS'],
      dtype=object)
In [77]:
shooting['location_desc'].unique()
Out[77]:
array(['PUBLIC HOUSE', 'APT BUILD', 'BAR/NIGHT CLUB', 'SHOE STORE',
       'PVT HOUSE', 'GROCERY/BODEGA', 'FAST FOOD', 'RESTAURANT/DINER',
       'COMMERCIAL BLDG', 'STORE UNCLASSIFIED', 'GAS STATION',
       'DRY CLEANER/LAUNDRY', 'CANDY STORE', 'VARIETY STORE',
       'STORAGE FACILITY', 'SUPERMARKET', 'BEAUTY/NAIL SALON',
       'CLOTHING BOUTIQUE', 'JEWELRY STORE'], dtype=object)
In [78]:
#visualizing query 1
q1 = pd.read_csv('/Users/vijitchekkala/Desktop/DAP/dap project/Q1.csv')
In [79]:
q1.head()
Out[79]:
count race_ethnicity boro
0 10126 Black Hispanic BRONX
1 15015 White Hispanic BRONX
2 2490 Black Hispanic BROOKLYN
3 8250 White Hispanic BROOKLYN
4 2988 Black Hispanic NEW YORK
In [80]:
plt.figure(figsize=(18,10))
sns.catplot(x="boro",y="count",kind='bar',hue='race_ethnicity',aspect=2,palette="Set3",
            edgecolor=sns.color_palette("muted"),data=q1)
Out[80]:
<seaborn.axisgrid.FacetGrid at 0x1c27904dd0>
<Figure size 1296x720 with 0 Axes>
In [81]:
#visualizing query 2 #cocaine use location wise deaths
q2 = pd.read_csv('/Users/vijitchekkala/Desktop/DAP/dap project/Q2.csv')
In [82]:
q2[q2['sex']=='Male']
Out[82]:
avg sex cocaine location
3 44.0 Male Y Hospital
4 56.0 Male Y Residence
6 44.0 Male Y Other
9 27.0 Male Y Hospital
12 30.0 Male Y Residence
13 35.0 Male Y Other
14 46.0 Male Y Residence
15 26.0 Male Y Other
16 34.0 Male Y Hospital
18 54.0 Male Y Residence
19 49.0 Male Y Residence
20 21.0 Male Y Hospital
21 60.0 Male Y Hospital
22 59.0 Male Y Residence
24 53.0 Male Y Residence
26 43.0 Male Y Residence
28 52.0 Male Y Hospital
32 56.0 Male Y Other
33 28.0 Male Y Other
35 35.0 Male Y Residence
38 43.0 Male Y Hospital
39 35.0 Male Y Hospital
43 36.0 Male Y Other
45 59.0 Male Y Hospital
46 41.0 Male Y Other
49 45.0 Male Y Hospital
55 46.0 Male Y Hospital
57 50.0 Male Y Residence
58 41.0 Male Y Hospital
59 41.0 Male Y Residence
60 46.0 Male Y Other
61 31.0 Male Y Hospital
64 34.0 Male Y Residence
67 40.0 Male Y Hospital
68 61.0 Male Y Hospital
74 43.0 Male Y Other
75 38.0 Male Y Other
77 24.0 Male Y Residence
80 48.0 Male Y Other
81 65.0 Male Y Other
84 68.0 Male Y Residence
86 51.0 Male Y Residence
87 48.0 Male Y Hospital
89 51.0 Male Y Hospital
90 28.0 Male Y Residence
91 44.0 Male Y Residence
93 39.0 Male Y Hospital
In [83]:
# Add title and axis
plt.figure(figsize=(16,8))
sns.countplot(x='sex',hue='location',palette="Set3",
              edgecolor=sns.color_palette("muted"),
              data=q2[q2['sex']=='Male']).set_title("Male deaths due to use of cocaine",fontsize=18)
Out[83]:
Text(0.5, 1.0, 'Male deaths due to use of cocaine')
In [84]:
#visualizing query 3 (drug,shoot,crime)
q3 = pd.read_csv('/Users/vijitchekkala/Desktop/DAP/dap project/Q3.csv')
In [85]:
plt.figure(figsize=(16,8))

g = sns.stripplot(x="boro",y="Hour",hue='location_desc',  palette='Set1',
                data=q3).set_title("Overall deaths happening at different locations")
plt.savefig('query 3')
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